内容简介：The big data analytics depend on the data mining and machine learning methods. In this talk, I will introduce our new advances of machine learning approaches including multi-label classification, deep learning, deep transfer learning and their applications in medical science, toxicity analysis, computer vision and Internet of Things. Experimental results show that these methods give better performance in terms of accuracy and efficiency. These methods can be generalized and applied to other areas of big data analytics.

报告人简介：Dr. Chaoyang Zhang is a tenured full professor of Computer Science in the School of Computing at the University of Southern Mississippi and has supervised thirteen Ph.D. students. He was the Director of School of Computing from 2008 to 2014. His research includes data mining, machine learning, big data analytics, systems biology and bioinformatics, medical data analysis and high performance computing. Dr. Zhang, as principal investigator or co-principle investigator, received eighteen research grants with a total of five million dollars, supported by US National Science Foundation, Department of Defense, National Institute of Health, Homeland Security and American Heart Association. Dr. Zhang has published more than eighty peer-reviewed journal articles and conference papers, one of which received the Sylvia Sorkin Greenfield Award, the best paper award of the Journal of Medical Physics, awarded by American Association of Physicists in Medicine in 2005. Dr. Zhang has been very active in academic service and leadership. He served on the several National Science Foundation panels. He also severed as ACM-BCB2010 Steering Committee Co-Chair, 2009 IJCBS conference program committee chair. Dr. Zhang was elected to serve as President of the US Midsouth Computational Biology and Bioinformatics Society (MCBIOS) in 2014-2015 and he received MCBIOS Academic Service Award in 2018.